Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Business
- Education
- Social Sciences
- Engineering
- Computer Science
- Environment
- Medical Sciences
- Biology
- Psychology
- Earth Sciences
- Sports and Recreation
- Design
- Electrical Engineering
- Arts and Literature
- Statistics
- Economics
- Law
- Linguistics
- Physics
- Humanities
- Materials Science
- Mathematics
- Chemistry
- 13 more »
- « less
-
engineering schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Fellow in Multi-Agent Path Planning for Autonomous Drone Operations
-
, developing optimisation and machine-learning methods for conflict detection, separation assurance, and collision-free flight-path planning, and estimating the maximum operational capacity under varying
-
, collaborative perception, mapping, obstacle avoidance, and multi-agent path-planning algorithms, and integrate these capabilities on physical drone platforms. The work will involve system integration
-
, autonomy, path planning, or field operations. An active U.S. Government security clearance. Instructions All applications should be submitted through Interfolio at https://apply.interfolio.com/193554 The
-
Assistance Training Hub (PATH) School of Social Work University of Illinois at Urbana-Champaign Located Statewide in Illinois Job Summary Serve as the subject matter expert on all curriculum development
-
foundations of path and behaviour planning, control and automated learning of autonomous vehicle systems. The AVS Lab's research is motivated by the goal of developing the next generation of intelligent
-
planning under uncertainty (m/w/d) 05.04.2023, Academic staff We are the Autonomous Vehicles Systems (AVS) Lab and are interested in the algorithmic foundations of path and behaviour planning, control
-
; autonomous decision-making; robot localization and navigation. Experience in one or more of the following: path planning, motion planning, trajectory optimization or model predictive control; reinforcement
-
guided dynamically by a vision system. Key areas of investigation include representation learning for deformable objects, reinforcement learning for path planning, and cross-domain alignment. The
-
S065 Job Code #20003969 Career path maker: https://www.purdue.edu/hr/careerpathmaker/ Who We Are Purdue is a community built on collaboration, with global perspectives, Boilermaker pride and endless